{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9c3a5e62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch    : 1.12.1\n",
      "lightning: 2022.9.15\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -p torch,lightning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "292759a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import lightning as L\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "import torchmetrics\n",
    "from lightning.pytorch.loggers import CSVLogger\n",
    "\n",
    "from shared_utilities import CustomDataModule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ef478510-97a2-497c-8831-bb594b753d85",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_epochs = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbcee9b9-40cf-4083-b36e-b09fe28e4ee2",
   "metadata": {},
   "source": [
    "### With Restarts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f9bf7772",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs/10)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "for i in range(num_epochs):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "plt.ylabel(\"Learning rate\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.plot(lrs);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce656fef-698a-4d9e-8a2e-0c4e8b67d01b",
   "metadata": {},
   "source": [
    "### Classic cosine annealing (decay per epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0271fa05-1191-4dfa-8f57-c1e9310112ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x293b54c70>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "\n",
    "for i in range(num_epochs):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "plt.plot(lrs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5603b4-e089-4489-a51c-1cb41cdf9d27",
   "metadata": {},
   "source": [
    "### Classic cosine annealing (decay per batch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6d9c70b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "\n",
    "\n",
    "dm = CustomDataModule()\n",
    "dm.setup(\"training\")\n",
    "num_steps = num_epochs * len(dm.train_dataloader())\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_steps)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "for i in range(num_steps):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "\n",
    "ax1 = plt.subplot(1, 1, 1)\n",
    "ax1.set_ylabel(\"Learning rate\")\n",
    "ax1.set_xlabel(\"Iterations\")\n",
    "ax1.plot(lrs)\n",
    "\n",
    "###################\n",
    "# Set second x-axis\n",
    "ax2 = ax1.twiny()\n",
    "newlabel = list(range(num_epochs+1))\n",
    "\n",
    "newpos = [e * (num_steps // num_epochs) for e in newlabel]\n",
    "\n",
    "ax2.set_xticks(newpos[::20])\n",
    "ax2.set_xticklabels(newlabel[::20])\n",
    "\n",
    "ax2.xaxis.set_ticks_position('bottom')\n",
    "ax2.xaxis.set_label_position('bottom')\n",
    "ax2.spines['bottom'].set_position(('outward', 45))\n",
    "ax2.set_xlabel('Epochs')\n",
    "ax2.set_xlim(ax1.get_xlim());\n",
    "\n",
    "plt.savefig('5-cosine-batch-decay_lr.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ce808943-a20e-44d2-9303-c897226b37df",
   "metadata": {},
   "outputs": [],
   "source": [
    "class PyTorchMLP(torch.nn.Module):\n",
    "    def __init__(self, num_features, num_classes):\n",
    "        super().__init__()\n",
    "\n",
    "        self.all_layers = torch.nn.Sequential(\n",
    "            # 1st hidden layer\n",
    "            torch.nn.Linear(num_features, 100),\n",
    "            torch.nn.BatchNorm1d(100),\n",
    "            torch.nn.ReLU(),\n",
    "            \n",
    "            # 2nd hidden layer\n",
    "            torch.nn.Linear(100, 50),\n",
    "            torch.nn.BatchNorm1d(50),\n",
    "            torch.nn.ReLU(),\n",
    "            \n",
    "            # output layer\n",
    "            torch.nn.Linear(50, num_classes),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = torch.flatten(x, start_dim=1)\n",
    "        logits = self.all_layers(x)\n",
    "        return logits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "59a6a00d",
   "metadata": {},
   "outputs": [],
   "source": [
    "class LightningModel(L.LightningModule):\n",
    "    def __init__(self, model, learning_rate, cosine_t_max):\n",
    "        super().__init__()\n",
    "\n",
    "        self.learning_rate = learning_rate\n",
    "        self.cosine_t_max = cosine_t_max\n",
    "        self.model = model\n",
    "\n",
    "        self.save_hyperparameters(ignore=[\"model\"])\n",
    "\n",
    "        self.train_acc = torchmetrics.Accuracy()\n",
    "        self.val_acc = torchmetrics.Accuracy()\n",
    "        self.test_acc = torchmetrics.Accuracy()\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "\n",
    "    def _shared_step(self, batch):\n",
    "        features, true_labels = batch\n",
    "        logits = self(features)\n",
    "\n",
    "        loss = F.cross_entropy(logits, true_labels)\n",
    "        predicted_labels = torch.argmax(logits, dim=1)\n",
    "        return loss, true_labels, predicted_labels\n",
    "\n",
    "    def training_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "\n",
    "        self.log(\"train_loss\", loss)\n",
    "        self.train_acc(predicted_labels, true_labels)\n",
    "        self.log(\n",
    "            \"train_acc\", self.train_acc, prog_bar=True, on_epoch=True, on_step=False\n",
    "        )\n",
    "        return loss\n",
    "\n",
    "    def validation_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "\n",
    "        self.log(\"val_loss\", loss, prog_bar=True)\n",
    "        self.val_acc(predicted_labels, true_labels)\n",
    "        self.log(\"val_acc\", self.val_acc, prog_bar=True)\n",
    "\n",
    "    def test_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.test_acc(predicted_labels, true_labels)\n",
    "        self.log(\"test_acc\", self.test_acc)\n",
    "\n",
    "    def configure_optimizers(self):\n",
    "        opt = torch.optim.SGD(self.parameters(), lr=self.learning_rate)\n",
    "        sch = torch.optim.lr_scheduler.CosineAnnealingLR(opt, T_max=self.cosine_t_max)\n",
    "\n",
    "\n",
    "        return {\n",
    "            \"optimizer\": opt,\n",
    "            \"lr_scheduler\": {\n",
    "                \"scheduler\": sch,\n",
    "                \"monitor\": \"train_loss\",\n",
    "                \"interval\": \"step\", # step means \"batch\" here, default: epoch\n",
    "                \"frequency\": 1, # default\n",
    "            },\n",
    "        }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "094b0c74-cf04-4395-83c1-22fbe94cb9c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightning.pytorch.callbacks import ModelCheckpoint\n",
    "\n",
    "callbacks = [\n",
    "    ModelCheckpoint(save_top_k=1, mode=\"max\", monitor=\"val_acc\", save_last=True)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e3e70623",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Global seed set to 123\n",
      "GPU available: True (mps), used: False\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8d3754c18ef548b58ad5a34b20dbc623",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Finding best initial lr:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_steps=100` reached.\n",
      "Learning rate set to 0.15848931924611143\n",
      "Restoring states from the checkpoint path at /Users/sebastianraschka/Desktop/cosine/.lr_find_06c03659-916d-4a11-bef4-3e6837d3c51e.ckpt\n"
     ]
    }
   ],
   "source": [
    "%%capture --no-display\n",
    "\n",
    "L.seed_everything(123)\n",
    "dm = CustomDataModule()\n",
    "\n",
    "pytorch_model = PyTorchMLP(num_features=100, num_classes=2)\n",
    "lightning_model = LightningModel(model=pytorch_model, learning_rate=0.1, cosine_t_max=num_steps)\n",
    "\n",
    "trainer = L.Trainer(\n",
    "    max_epochs=num_epochs,\n",
    "    auto_lr_find=True,\n",
    "    accelerator=\"cpu\",\n",
    "    devices=\"auto\",\n",
    "    logger=CSVLogger(save_dir=\"logs/\", name=\"my-model\"),\n",
    "    deterministic=True,\n",
    "    callbacks=callbacks\n",
    ")\n",
    "\n",
    "results = trainer.tune(model=lightning_model, datamodule=dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0542570a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/cb/1y0v6fzx5c54sztp5nqq39jc0000gn/T/ipykernel_2773/735961897.py:3: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = results[\"lr_find\"].plot(suggest=True)\n",
    "# fig.savefig(\"lr_suggest.pdf\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e9293189",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.15848931924611143\n"
     ]
    }
   ],
   "source": [
    "# get suggestion\n",
    "new_lr = results[\"lr_find\"].suggestion()\n",
    "print(new_lr)\n",
    "\n",
    "# update hparams of the model\n",
    "lightning_model.hparams.learning_rate = new_lr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "eb1581b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  | Name      | Type       | Params\n",
      "-----------------------------------------\n",
      "0 | model     | PyTorchMLP | 15.6 K\n",
      "1 | train_acc | Accuracy   | 0     \n",
      "2 | val_acc   | Accuracy   | 0     \n",
      "3 | test_acc  | Accuracy   | 0     \n",
      "-----------------------------------------\n",
      "15.6 K    Trainable params\n",
      "0         Non-trainable params\n",
      "15.6 K    Total params\n",
      "0.062     Total estimated model params size (MB)\n"
     ]
    },
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       "version_major": 2,
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      "text/plain": [
       "Sanity Checking: 0it [00:00, ?it/s]"
      ]
     },
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    },
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      "text/plain": [
       "Training: 0it [00:00, ?it/s]"
      ]
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "283c098fcef54988a8155ae4e6ca83ae",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1781846c38204e8899026aa90f61bb12",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8a0d04ba5d10416eb7cc221866c4ec4b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_epochs=200` reached.\n"
     ]
    }
   ],
   "source": [
    "trainer.fit(model=lightning_model, datamodule=dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4c6fa764",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "metrics = pd.read_csv(f\"{trainer.logger.log_dir}/metrics.csv\")\n",
    "\n",
    "aggreg_metrics = []\n",
    "agg_col = \"epoch\"\n",
    "for i, dfg in metrics.groupby(agg_col):\n",
    "    agg = dict(dfg.mean())\n",
    "    agg[agg_col] = i\n",
    "    aggreg_metrics.append(agg)\n",
    "\n",
    "df_metrics = pd.DataFrame(aggreg_metrics)\n",
    "df_metrics[[\"train_loss\", \"val_loss\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"Loss\"\n",
    ")\n",
    "\n",
    "\n",
    "df_metrics[[\"train_acc\", \"val_acc\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"ACC\"\n",
    ")\n",
    "\n",
    "plt.ylim([0.7, 1.0])\n",
    "\n",
    "plt.savefig('5-cosine-batch-decay_acc.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0df61ef8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at logs/my-model/version_12/checkpoints/epoch=150-step=67950.ckpt\n",
      "Loaded model weights from checkpoint at logs/my-model/version_12/checkpoints/epoch=150-step=67950.ckpt\n",
      "/Users/sebastianraschka/miniforge3/envs/dl-fundamentals/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:231: PossibleUserWarning: The dataloader, test_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 10 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
      "  rank_zero_warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3e776f79d16541ad9b7237c0663741ad",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">         test_acc          </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8952500224113464     </span>│\n",
       "└───────────────────────────┴───────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36m        test_acc         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8952500224113464    \u001b[0m\u001b[35m \u001b[0m│\n",
       "└───────────────────────────┴───────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[{'test_acc': 0.8952500224113464}]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=lightning_model, datamodule=dm, ckpt_path=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1c17a3c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at logs/my-model/version_12/checkpoints/last.ckpt\n",
      "Loaded model weights from checkpoint at logs/my-model/version_12/checkpoints/last.ckpt\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "09493f89b5114a4398cecc40772cc3ec",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">         test_acc          </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8967499732971191     </span>│\n",
       "└───────────────────────────┴───────────────────────────┘\n",
       "</pre>\n"
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      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36m        test_acc         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8967499732971191    \u001b[0m\u001b[35m \u001b[0m│\n",
       "└───────────────────────────┴───────────────────────────┘\n"
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    },
    {
     "data": {
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       "[{'test_acc': 0.8967499732971191}]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=lightning_model, datamodule=dm, ckpt_path=\"last\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "c76a0675-77d4-4008-8b96-4ac4846ee829",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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